Asmaa Bialy - Academia.edu (original) (raw)

Papers by Asmaa Bialy

Al-Mağallah Al-ʿilmiyyaẗ Li Kulliyyaẗ Al-Tarbiyyaẗ Al-Nawʿiyyaẗ - Ǧāmiʿaẗ Dumyāṭ, Jun 1, 2024

المجلة العلمية لكلية التربية النوعية, 2024

This paper proposes a way to develop a machine translation system based on deep learning for the ... more This paper proposes a way to develop a machine translation system based on deep learning for the translation of Arabic texts into English. This system is for translating texts in the computer field, The proposed system contains six main stages and the system will be included in a database containing a bilingual dictionary (Arabic-English) containing terms in the field of Computer-based, the system was evaluated by human experts in addition to using the bleu scale, The system has been evaluated by comparing between manual and automatic translation and some measurements are used especially bleu measure. The manual translation is done by two human experts to check the translation quality in terms of the general form, content meaning, coherence of the phrases, and completeness of the. The final results proved that the proposed method achieved higher performance than other systems.

International Journal of Computer Applications, 2018

International journal of computer applications, Apr 17, 2018

This paper proposes an automatic text summarization method, which is considered as a selective pr... more This paper proposes an automatic text summarization method, which is considered as a selective process for the most important information in the original text. It could be divided into two types extractive and abstractive. In this study, a system for single documents text summarization is introduced to be used for Arabic text that rely on extractive method. According to this, we will go three stages, which are preprocessing phase, scoring of sentence, and summery generation. The pre-processing phase starts by removing punctuation marks, stop words, unifies synonyms as well as stemming words to obtain root form. Then it measures every sentence according to a collection of features in order to get the sentences with a higher score to be included in the final summary. The system has been evaluated by comparing between manual and automatic summarizations and some measurements are used especially Rouge measure. Manual summarize is done by two human experts to check the summaries' quality in terms of the general form, content, coherence of the phrases, lack of elaboration, repetition, and completeness of the meaning. The final results proved that the proposed method achieved the higher performance than other systems.

International Journal of Computer Applications, 2018

This paper proposes an automatic text summarization method, which is considered as a selective pr... more This paper proposes an automatic text summarization method, which is considered as a selective process for the most important information in the original text. It could be divided into two types extractive and abstractive. In this study, a system for single documents text summarization is introduced to be used for Arabic text that rely on extractive method. According to this, we will go three stages, which are pre-processing phase, scoring of sentence, and summery generation. The pre-processing phase starts by removing punctuation marks, stop words, unifies synonyms as well as stemming words to obtain root form. Then it measures every sentence according to a collection of features in order to get the sentences with a higher score to be included in the final summary. The system has been evaluated by comparing between manual and automatic summarizations and some measurements are used especially Rouge measure. Manual summarize is done by two human experts to check the summaries' quality in terms of the general form, content, coherence of the phrases, lack of elaboration, repetition, and completeness of the meaning. The final results proved that the proposed method achieved the higher performance than other systems.

Studies in Computational Intelligence, 2019

This paper presents a method based on natural language processing (NLP) for single Arabic documen... more This paper presents a method based on natural language processing (NLP) for single Arabic document summarization. The suggested method based on the extractive method to select the most valuable information in the document. However, working with Arabic text is considered as a challenging task, this chapter tries to produce an accurate result by using some of NLP techniques. The proposed method is formed from three phases, the first one work as a pre-processing phase to unify synonyms terms, stemming, remove punctuation marks and remove text decoration. Consequently, it produces the features vectors and scores these features to start to select the clauses with the highest scores then marks it as important clauses. The suggested method’s results are compared versus the traditional methods. In this context, two human experts summarized all the datasets manually in order to prepare a strong compare and effective evaluation of the suggested method. In the evaluation phase, some of the performance measures include accuracy, precision, recall, f-measure, and Rouge measure are used. The experimental results denoted that the suggested method showed a competitive execution compared with the human experts in summarization ratio as well as in the accuracy of the produced document.

Al-Mağallah Al-ʿilmiyyaẗ Li Kulliyyaẗ Al-Tarbiyyaẗ Al-Nawʿiyyaẗ - Ǧāmiʿaẗ Dumyāṭ, Jun 1, 2024

المجلة العلمية لكلية التربية النوعية, 2024

This paper proposes a way to develop a machine translation system based on deep learning for the ... more This paper proposes a way to develop a machine translation system based on deep learning for the translation of Arabic texts into English. This system is for translating texts in the computer field, The proposed system contains six main stages and the system will be included in a database containing a bilingual dictionary (Arabic-English) containing terms in the field of Computer-based, the system was evaluated by human experts in addition to using the bleu scale, The system has been evaluated by comparing between manual and automatic translation and some measurements are used especially bleu measure. The manual translation is done by two human experts to check the translation quality in terms of the general form, content meaning, coherence of the phrases, and completeness of the. The final results proved that the proposed method achieved higher performance than other systems.

International Journal of Computer Applications, 2018

International journal of computer applications, Apr 17, 2018

This paper proposes an automatic text summarization method, which is considered as a selective pr... more This paper proposes an automatic text summarization method, which is considered as a selective process for the most important information in the original text. It could be divided into two types extractive and abstractive. In this study, a system for single documents text summarization is introduced to be used for Arabic text that rely on extractive method. According to this, we will go three stages, which are preprocessing phase, scoring of sentence, and summery generation. The pre-processing phase starts by removing punctuation marks, stop words, unifies synonyms as well as stemming words to obtain root form. Then it measures every sentence according to a collection of features in order to get the sentences with a higher score to be included in the final summary. The system has been evaluated by comparing between manual and automatic summarizations and some measurements are used especially Rouge measure. Manual summarize is done by two human experts to check the summaries' quality in terms of the general form, content, coherence of the phrases, lack of elaboration, repetition, and completeness of the meaning. The final results proved that the proposed method achieved the higher performance than other systems.

International Journal of Computer Applications, 2018

This paper proposes an automatic text summarization method, which is considered as a selective pr... more This paper proposes an automatic text summarization method, which is considered as a selective process for the most important information in the original text. It could be divided into two types extractive and abstractive. In this study, a system for single documents text summarization is introduced to be used for Arabic text that rely on extractive method. According to this, we will go three stages, which are pre-processing phase, scoring of sentence, and summery generation. The pre-processing phase starts by removing punctuation marks, stop words, unifies synonyms as well as stemming words to obtain root form. Then it measures every sentence according to a collection of features in order to get the sentences with a higher score to be included in the final summary. The system has been evaluated by comparing between manual and automatic summarizations and some measurements are used especially Rouge measure. Manual summarize is done by two human experts to check the summaries' quality in terms of the general form, content, coherence of the phrases, lack of elaboration, repetition, and completeness of the meaning. The final results proved that the proposed method achieved the higher performance than other systems.

Studies in Computational Intelligence, 2019

This paper presents a method based on natural language processing (NLP) for single Arabic documen... more This paper presents a method based on natural language processing (NLP) for single Arabic document summarization. The suggested method based on the extractive method to select the most valuable information in the document. However, working with Arabic text is considered as a challenging task, this chapter tries to produce an accurate result by using some of NLP techniques. The proposed method is formed from three phases, the first one work as a pre-processing phase to unify synonyms terms, stemming, remove punctuation marks and remove text decoration. Consequently, it produces the features vectors and scores these features to start to select the clauses with the highest scores then marks it as important clauses. The suggested method’s results are compared versus the traditional methods. In this context, two human experts summarized all the datasets manually in order to prepare a strong compare and effective evaluation of the suggested method. In the evaluation phase, some of the performance measures include accuracy, precision, recall, f-measure, and Rouge measure are used. The experimental results denoted that the suggested method showed a competitive execution compared with the human experts in summarization ratio as well as in the accuracy of the produced document.